A deep tech start -up called in Singapore Skis senses An AI -powered platform that helps semiconductor manufacturers predict and detect potential chip defects on production lines in real time.
It has raised $ 8.5 million in Series A, making its total funding about $ 12 million. The period was led by the peak XV (formerly Sequoia India and C), which included Alpha Intelligence Capital, Fab, and others.
Established in 2018 by Engineers Akshasha Jagwani (CTO) and Owani Agarwal (CEO), the aim of the sexymine is to tackle a basic challenge in manufacturing semiconductor: raw production data, from images of defects to the products of the goods, to improve the real -time vision and improve the quality of the product.
Despite the total volume of data generated on the Fab floor, the one who stood in front of the co -founders was a wonderful lack of real -time intelligence.
Akanasha brings deep understanding of manufacturing, quality control, and software automation through building his experience such as automation solutions for manufacturers such as Hyundai Motors and GE and LED product development in Startups such as Embibib. Agarwal added a technical experience from his time to the visa, where he created a large -scale data analtics system, some of which were later secured as a trade secret. A skilled coder with a strong background in mathematics, she has long been interested in applying AI to traditional industries beyond Fantake.
Together, the pair reviewed the fields from aviation to automotive before landing on the semiconductors. Agarwal told Tech Crunch that despite the reputation of the semi -conductor industry, the inspection process remains widespread and scattered. He added that after talking to more than 50 engineers, it became clear that there was a significant scope to modernize how quality checks were made.
Today, FBS Dashboards, SPC charts, and inline inspection systems are filled today, but mostly only show data without analysis, Agarwal said. “The decision -making IT still burdenses on engineers: (they must investigate the spot patterns, irregularities, and detect the cause of the root. It is time to demand, sophix and not improve with the complexity of the growing process.”
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Six senses provide initial warnings to engineers to resolve potential issues such as defective detection, root cause analysis, and predicted failure.
Agarwal said the sexy platform is also designed to be used especially by process engineers rather than data scientists. “Processed engineers can fix the model using their own fab data, deploy them in less than two days, and rely on the results-without writing a line of all code. That’s why the platform makes the platform powerful and practical.”
Competitive landscapes include engineering teams at home, such as Kaganx and Halcone, inspection equipment integrating AI into their system, and startups, including Landing Dot AI and Robovision.
Sexyne’s AI platform is already in use in large semiconductor manufacturers such as Global Foundaries and JCET, which has been processed by more than 100 million chips to date. The founders said that consumers have reported a 30 % high production cycle, a 1-2 % increase in production, and a 90 % reduction in manual inspection work. This system is compatible with inspection equipment that covers more than 60 % of the global market.
Agarwal said, “Our target users are large quantities of chip makers. Including foundry, outsourced semiconductor assembly and test providers (OSATS), and integrated device manufacturers (IDM).” “We are already working with Fabs in Singapore, Malaysia, Taiwan and Israel, and are now spreading to the United States.”
Geographical political tensions, especially between the United States and China, where chips are made, are being given a new look, which is running new manufacturing investment all over the world.
“We are seeing that Fabs and Osat are spreading aggressively in Malaysia, Singapore, Vietnam, India and the United States.